A Usability Evaluation on the Visualization of Information Extraction Output

정보추출결과의 시각화 표현방법에 관한 이용성 평가 연구

  • 이지연 (연세대학교 문헌정보학과)
  • Published : 2005.06.01


The goal of this research is to evaluate the usability of visually browsing the automatically extracted information. A domain-independent information extraction system was used to extract information from news type texts to populate the visually browasable knowledge base. The information extraction system automatically generated Concept-Relation-Concept triples by applying various Natural Language Processing techniques to the text portion of the news articles. To visualize the information stored in the knowledge base, we used PersoanlBrain to develop a visualization portion of the user interface. PersonalBrain is a hyperbolic information visualization system, which enables the users to link information into a network of logical associations. To understand the usability of the visually browsable knowledge base, IS test subjects were observed while they use the visual interface and also interviewed afterward. By applying a qualitative test data analysis method. a number of usability Problems and further research directions were identified.


Information Visualzation;Information Extraction;Usability Evaluation;Qualitative Evaluation


  1. 이지연. 2001. 키워드탐색과 비주얼 브라우징을 이용한 이미지 검색 시스템. '한국정보관리학회지', 18(4): 183-200
  2. Allen, M. 2002. 'The Hype over Hyperbolic Browsers.' Online, 26(3): 20-28
  3. Paik, W. and Lee, J. 2004. 'Extracting Legal Propositions from Appellate Decisions with Text Discourse Analysis Methods.' Lecture Notes in Computer Science (LNCS), Vol. 3292, Springer-Verlag: 621-633
  4. Marchionini, G. 1987. 'An Invitation to Browse: Designing Full-Text Systems for Novice Users.' The Canadian Journal for Information Science, 12 (3-4): 125-138
  5. Sowa, J. 1984. Conceptual Structures: Information Processing in Mind and Machine, Reading. MA: Addison-Wesley
  6. Lynch, C. 1991. 'The Technologies of Electronic Imaging.' Journal of American Society for Information Science, 42(8): 578-585<578::AID-ASI7>3.0.CO;2-U
  7. Spence, R. 2001. Information Visualization. New York: ACM Press
  8. Marchionini, G. 1988. 'Hypermedia and Learning: Freedom and Chaos.' Educational Technology, 28(11): 8-12
  9. 서은경. 2002. 정보시각화에 대한 스킴모형별 비교 분석. 한국문헌정보학회지, 36(4): 176-205
  10. Sager, N., Friedman, C., & Lyman, M.S. 1987. Medical Language Processing: Computer Management of Narrative Data, Reading. MA: Addison-Wesley
  11. Ware, C. 2004. Information Visualization: Perception for Design. San Francisco: Morgan Kaufmann
  12. Paik, W. 2000. CHronological information Extraction SyStem (CHESS). PhD Dissertation, Syracuse University, Syracuse, NY
  13. Santorini, B. 1990. 'Part-of-speech Tagging Guidelines for the Penn Treebank Project.' Technical report, Department of Computer & Information Science, U. of Penn
  14. Schank, R. 1972. 'Conceptual Dependency: A Theory of Natural Language Understanding.' Cognitive Psychology, 3(4): 552-631
  15. Bederson, B. and Shneiderman, B. 2003. The Craft of Information Visualization: Readings and Reflections. San Francisco: Morgan Kaufmann

Cited by

  1. A MVC Framework for Visualizing Text Data vol.20, pp.2, 2014,